Triglyceride‐glucose index and clinical outcomes in sepsis: A retrospective cohort study of MIMIC‐IV

Abstract Although accumulating researches were done for investigating the relationship between triglyceride‐glucose index (TyG index) and different diseases, none of the researches have been made in sepsis yet. In this study, we aimed to explore the relationship between TyG index and clinical outcomes in sepsis based on a large critical care public database. Sepsis patients in Medical Information Mart for Intensive Care IV (MIMIC‐IV) Database were included. The exposure was TyG index, which was calculated by the equation: ln (TG (mg/dL) × FBG (mg/dL)/2). The outcomes were in‐hospital mortality and 1‐year mortality. The relationship between TyG index and outcomes was performed by Cox regression analysis. Smooth fitting curves were constructed by using generalized additive model. Kaplan–Meier analyses for cumulative hazard of 1‐year mortality in different groups were done. 1103 sepsis patients were included with a median TyG index of 9.78. The mortalities of in‐hospital and 1‐year were 37.53% (n = 414) and 42.25% (n = 466), respectively. After adjusting confounders, there was a significantly negative relationship between TyG index and mortalities of in‐hospital and 1‐year. With the per unit increment in TyG index, the risk of in‐hospital and 1‐year mortality both decreased by 21% (HR = 0.79, 95% CI: 0.66–0.94, p = 0.0086 and HR = 0.79, 95% CI: 0.66–0.94, p = 0.0080, respectively). A negative relationship between TyG index and clinical outcomes in sepsis was found.

stroke.Moreover, the ischemic stroke patients with higher levels of TyG index had poorer outcomes. 6In patients who had chronic kidney diseases and coronary artery diseases, the relationship between TyG index and the risk of 1-year mortality was significantly positive (hazard ratio (HR) =1.343, p < 0.05). 7However, some other researches found there might be a U-shape relationship between TyG index and some diseases.A public database research included 9254 middle age and elderly participants and illuminated that those participants with the third quartile level of TyG index had the minimal risk of all-cause mortality. 8e longitudinal analysis including 11,851 participants with a median follow-up of 24.26 years in China concluded that there was a U-shape association between TyG index and the morbidity of atrial fibrillation. 9 the US participants, the relationship between TyG index and the morbidity of diabetic retinopathy was also the U-shape. 10wever, none of the researches have been made in sepsis yet.
In this study, we aimed to discuss the possible relationship between TyG index and outcomes of short-term and long-term in sepsis based on a large critical care public database.

| Database and patients
2][13] All sepsis patients with sepsis 3.0 criteria were included. 14Exclusion criteria were as follows: (1) Without records of FBG and TG in 24 h after admission; (2) Age less than 18-year-old; (3) Diabetes and patients with antidiabetic treatment (insulin or oral antidiabetics); (4) Died within 48 h after admission; (5) Patients with acute pancreatitis; (6) Patients with dyslipidemia and patients with receiving lipid-lowering drugs.
Flow chart was demonstrated in Figure S1.Initially, sepsis patients with both FBG and TG levels in 24 h after admission were included (n = 1767).After excluding some patients, 1103 sepsis patients were included in the final cohort.

| Variables and parameters
Baseline characteristics were included within 24 h after admission as follows: age, gender, marital status, ethnicity, managements and therapies including renal replacement therapy (RRT), ventilator use and vasopressor use, organ dysfunction including septic shock and acute kidney function (AKI), length of stay (LOS) in ICU and hospital, disease severity scores, comorbidities, vital signs and laboratory parameters.

| Statistical analysis
We used and the packages R (http:// www.R-proje ct.org) software and the EmpowerStats (http:// www.empow ersta ts.com) software for performing statistical analysis.Statistical significance was confirmed while there was a two-sides p < 0.05.
First, based on the in-hospital mortality, the cohort was divided into survivor group and non-survivor group.Second, based on the tertiles of TyG index, the cohort was divided into three different groups (T1: <9.47, T2: 9.47-10.16,T3: >10.16).General characteristics were compared.Continuous and categorical parameters were indicated as the median with interquartile ranges and the percentages, respectively.The methods of Mann-Whitney U-test or chi-squared test were applied.Third, Cox regression analysis was performed to investigate the relationship between TyG index and prognosis in sepsis patients.
We constructed three different models including Crude model (adjusting for none), Model A (adjusting for age and gender) and Model B (a fully adjusted model).TyG index was investigated not only as a continuous variable but also as a categorial variable (tertiles: T1--T3; quartiles: Q1-Q4 (Q1: <9.27, Q2: 9.27-9.77,Q3: 9.78-10.39,Q4: >10.39)).showing the relationship between TyG index and prognosis by using generalized additive model.In addition, Kaplan-Meier analyses were made for cumulative hazard of 1-year mortality in sepsis patients in different groups (T1-T3, Q1-Q4).Finally, we also did the subgroups analysis for figuring out the stability of our results.

| General characteristics of the study cohort
In this study, 1103 sepsis patients were included based on inclusion and exclusion criteria.The median age was 61-years-old, 58.20% were males, 42.16% were married and 64.55% were White (Table S1).The proportions of RRT, ventilation use and vasopressor use during hospitalization were 23.12%, 80.96% and 32.18%, respectively.The incidences of septic shock and AKI during hospitalization were 44.70% and 77.33%, respectively.The mortalities of in-hospital and 1-year were 37.53% (n = 414) and 42.25% (n = 466), respectively.were significantly higher in non-survivor group.

| Comparison of the linear model and the non-linear model
We compared the linear model (model I) and non-linear model (model II) in Table 4.For in-hospital mortality, the linear model was better (p for the log-likelihood ratio test = 0.080).When TyG index ≤9.33, the risk of in-hospital mortality significantly decreased with the increment in TyG index (HR = 0.49, 95% CI: 0.27-0.87,p = 0.0145).When TyG index >9.33,there was also a negative relationship, but without statistically significant (HR = 0.91, 95% CI: 0.72-1.15,p = 0.4259).

| Subgroup analysis
In Table S2, we also constructed the subgroup analysis.Chloride, RBC and sodium were found to be interacted with the relationship between TyG index and in-hospital mortality (p for interaction: 0.0207, 0.0217 and 0.0321, respectively).Chloride and sodium were found to be interacted with the relationship between TyG index and 1-year mortality (p for interaction: 0.0346 and 0.0368, respectively).

| DISCUSS ION
In the present study, some points have been addressed.First, the negative relationship between TyG index and clinical outcomes in sepsis was found.Second, with the per unit increment in TyG index, the risk of in-hospital and 1-year mortality in sepsis both decreased by 21%.
We found a negative association between TyG index and mortalities of in-hospital and 1-year in sepsis.It might be inconsistent with previous studies which have done in some other diseases.The general characteristic of the sepsis cohort could partly explain the results.In our study, patients in non-survivor group had lower levels of TyG index (Table 1).Non-survivor group patients were older with higher levels of variables including total bilirubin, total calcium, PT, PTT, lactate and lower levels of chloride, haematocrit and haemoglobin.In addition, the incidence of septic shock and AKI were higher in non-survivor group.
Since the TyG index was combined with TG and FBG, some explanations about the negative association between TyG index and outcomes in sepsis could be made on the both sides of TG and FBG.
[17] The prognostic value of TG in sepsis has been seldom discussed yet, and some researches found that lower levels of TG were F I G U R E 1 Smooth fitting curves demonstrated the associations between TyG index and mortalities of in-hospital (A) and 1-year (B).associated with higher risk of poor prognosis in neurocardiac diseases.One study in myocardial infarction revealed that TG < 110 mg/ dL was confirmed as the cut-off value for predicting 30-day mortality (HR = 5.05, 95% CI: 1.75-14.54). 18Moreover, decreased level of TG was an indicator of recurrent ischemia in myocardial infarction. 19 heart failure patients, with TG levels decreasing, the risk of cardiac death increased. 20One prospective cohort study among 27,937 female participants with a median of 19.3 years' follow-up concluded that participants with the lowest quartile levels of TG had the highest morbidity of hemorrhagic stroke compared with those participants in the top quartile of TG. 21wer levels of FBG have been found to be associated with outcomes in sepsis and non-sepsis diseases.A systemic review including more than one hundred prospective researches with more than 2 million participants clarified that when the level of FBG less than 4.0 mmol/L, the risks of stroke, cardiovascular events and all-cause mortality increased significantly (HR = 1.08, 95% CI:  significantly related with a higher 1-year cumulative mortality rate in sepsis patients. 24sed on the previous related researches, the possible mechanism of the negative relationship between TyG index and prognosis in sepsis could be illuminated as follow.First, TG is a significant energy source for tissues and organs.Lower TyG index might be correlated to a worse nutrition status, which could contribute to the worsening of sepsis. 25Second, evidences proved that there was a close relationship between sympathetic activity and the regulation and metabolism of TG. 19 Decreased plasma TG in the early stage of sepsis could be an indicator of enhanced sympathetic activity, which in turn may increase the risk of poor prognosis.[28][29] The strength of our study was that we found a negative relationship between TyG index and clinical outcomes in sepsis patients.
However, our study had some limitations.First, the relationship between TyG index and outcomes in sepsis was not cause-effect.
Second, we only used the one time of TyG index and didn't dynamically evaluate the TyG index.TyG index might be affected by medications and progression of sepsis.Third, it was a retrospective study based on a public database, so we couldn't rule out all confounding factors.
current study, and so are not publicly available.Data are however available from the authors upon reasonable request and with permission of the Massachusetts Institute of Technology (MIT) and Beth Israel Deaconess Medical Center (BIDMC).

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Ning Ding https://orcid.org/0000-0001-7805-2191 Fourth, Model I (linear model) and Model II (non-linear model) were compared.If the p value <0.05, model II was the better.Otherwise, Model I was better.Fifth, smooth fitting curves were performed for

F I G U R E 2 | 9 of 10 CAO
Kaplan-Meier analysis for cumulative hazard of 1-year mortality in sepsis based on tertiles (A) and quartiles (B) of TyG index.et al.

Table 1
showed the different variables in the study cohort.The me-

| 3 of 10 CAO et al. TA B L E 1
Clinical characteristics between survivor group and non-survivor group based on in-hospital mortality.
Clinical characteristics between three groups based on tertiles of TyG index.AKI, acute kidney injury; ALT, alanine aminotransferase; APACHE, acute physiology and chronic health evaluation; AST, aspartate aminotransferase; CAD, coronary artery disease; DBP, diastolic blood pressure; FBG, fasting blood sugar; HR, heart rate; ICU, intensive care unit; INR, international normalized ratio; IQR, interquartile ranges; OS, length of stay; PLT, platelet; PT, prothrombin time; PTT, partial thrombin time; RBC, red blood cells; RDW, red blood cell distribution width; RR, respiratory rate; RRT, renal replacement therapy; SBP, systolic blood pressure; SOFA, sequential organ failure assessment; TG, triglyceride; TyG index, triglyceride glucose index; WBC, white blood cells.Associations between TyG index and mortalities of in-hospital and 1-year in crude and adjusted models.